| | | 20,000+ Fresh Resumes Monthly | |
|
|
| |
Click here or scroll down to respond to this candidateCandidate's Name
Data AnalystMissouri Mob - PHONE NUMBER AVAILABLE Email- EMAIL AVAILABLESUMMARY Dedicated and results-driven Data Analyst with 5+ years of experience in leveraging data analytics to drive business solutions in the healthcare and financial sectors. Proven track record of extracting insights from complex datasets, improving operational efficiencies, and delivering actionable recommendations. Proficient in a wide range of analytical tools and technologies, with expertise in SQL, Python, Tableau, and statistical modeling. Expertise in analyzing large datasets using SQL and Python to derive meaningful insights and trends. Proficient in data visualization tools such as Tableau and Power BI to create interactive dashboards and reports for stakeholders, enabling data-driven decision-making. Strong statistical background with hands-on experience in applying predictive modeling techniques to forecast trends, optimize resource allocation, and identify growth opportunities. Skilled in using R and Python libraries (pandas, scikit-learn) for advanced analytics and machine learning. Developed and maintained BI solutions to track KPIs, monitor business performance, and provide actionable insights. Experience in designing automated reporting systems and executive dashboards to streamline information dissemination across departments. Proficient in managing data pipelines and ETL processes, ensuring data integrity and reliability. Hands-on experience with cloud-based data platforms (AWS, Google Cloud) and SQL-based databases (MySQL, PostgreSQL) for efficient data storage and retrieval. Effective communicator and team player, collaborating with cross-functional teams including IT, operations, and finance to translate business requirements into analytical solutions. Proven ability to present complex technical concepts to non- technical stakeholders.SKILLSMethodologies: SDLC, Agile, WaterfallProgramming Language: Python, SQL, Java, RPackages: NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, TensorFlow, Seaborn Visualization Tools: Tableau, Power BI, Advanced Excel (Pivot Tables, VLOOKUP) IDEs: Visual Studio Code, PyCharm, Jupyter Notebook, IntelliJ Cloud Platforms: Amazon Web Services (AWS), Google Cloud Platform (GCP) Database: MySQL, PostgreSQL, MySQL, MongoDB, T-SQL Other Technical Skills: SISS, SSRS, Machine Learning Algorithms, Probability distributions, Confidence Intervals, ANOVA, Hypothesis Testing, Regression Analysis, Linear Algebra, Advance Analytics, Data Mining, Data Visualization, Data warehousing, Data transformation, Data Storytelling, Association rules, Clustering, Classification, Regression, A/B Testing, Forecasting & Modelling, Data Cleaning, Data Wrangling, JiraVersion Control Tools: Git, GitHubOperating Systems: Windows, Linux, Mac iOSEDUCATIONM.S in Computer Science - University of Missouri, Kansas City, MO B.Tech. in Information Technology Sreenidhi Institute of Science and Technology. CERTIFICATIONMicrosoft certified: Azure Data Engineer Associate. IBM Data Science Professional Certificate.EXPERIENCELabcorp, MO Jun23 - Current Data Analyst Analyzing complex healthcare datasets using SQL and Python (pandas and numpy) to extract actionable insights crucial for optimizing patient care protocols and operational efficiencies. Developing interactive dashboards and reports in Tableau that visually represent key healthcare metrics such as patient outcomes, treatment efficacy, and resource utilization, aiding informed decision-making by clinical & administrative teams. Orchestrating ETL processes to meticulously manage and enhance the quality of healthcare data, ensuring utmost accuracy and integrity for regulatory compliance and clinical decision support. Employing advanced statistical tools (SAS, SPSS) to perform predictive modeling and sophisticated analyses of clinical data, forecasting patient trends and healthcare resource demands to preemptively address care needs. Conducting ongoing monitoring and reporting on critical clinical performance metrics, enabling real-time insights into healthcare delivery effectiveness and quality metrics. Leveraging AWS for cloud-based data storage, processing, and analytics, optimizing scalability and performance of healthcare data infrastructure. Applying predictive modeling techniques to forecast patient demand, leading to a 30% decrease in waiting times and a 25% increase in patient satisfaction scores. Applying machine learning algorithms to healthcare datasets for predictive analytics, enhancing diagnostic accuracy and treatment planning efficacy in clinical settings. Enforcing strict adherence to healthcare regulations, including HIPAA, in all aspects of data management and analysis to safeguard patient privacy and confidentiality. Leveraging expertise in healthcare information systems (Epic) to integrate and analyze electronic health records (EHR), supporting comprehensive patient care insights and longitudinal studies. Conducting monthly monitoring and reporting on clinical performance metrics, contributing to a 10% improvement in adherence to clinical protocols.Cognizant, India May18 Aug22 Data Analyst Engineered scalable data pipelines and ETL processes for financial data integration, resulting in a 30% reduction in data processing time and improved data accuracy for regulatory reporting. Designed and implemented data warehouses on AWS Redshift to consolidate financial data from multiple sources, enabling faster query performance and real-time analytics for investment analysis and risk management. Developed Python scripts for data transformation and cleansing, automating daily reconciliation processes for financial transactions, reducing manual effort by 50%. Led the migration of legacy financial systems to cloud-based solutions (AWS, GCP), enhancing data availability and scalability while ensuring security and compliance with industry regulations (GDPR, PCI-DSS). Collaborated with cross-functional teams including finance, IT, and compliance to implement data governance policies and frameworks, ensuring data integrity and confidentiality in financial data handling. Implemented data lineage and metadata management solutions using Informatica and Collibra, facilitating auditability and traceability of financial data for regulatory audits and internal reviews. Developed data models and dashboards in Power BI to visualize financial performance metrics (revenue growth, cost analysis), enabling executive decision-making and strategic planning. Conducted performance tuning of SQL queries and Hadoop jobs to optimize data processing and report generation, achieving 20% faster turnaround time for financial reporting cycles. Participated in Agile scrum ceremonies to prioritize and deliver data engineering tasks aligned with business requirements, contributing to on-time project delivery and customer satisfaction. Mentored junior team members in best practices for data engineering and financial domain knowledge, enhancing team capabilities and knowledge sharing within the organization. |
